{
npx skills add https://github.com/tony-zhelonkin/SciAgent-toolkit --skill single-cell-rna-qc-tony-zhelonkin
Please help me install this Agent Skill. Skill: single-cell-rna-qc Source: https://github.com/tony-zhelonkin/SciAgent-toolkit/tree/main/skills/single-cell-rna-qc Command: npx skills add https://github.com/tony-zhelonkin/SciAgent-toolkit --skill single-cell-rna-qc-tony-zhelonkin
MAD-based quality control for single-cell RNA-seq data provides adaptive, data-driven thresholds for commonly used QC metrics, reducing reliance on fixed cutoffs.
Run the MAD-based QC workflow on your raw data to filter low-quality cells and generate QC plots prior to normalization.
High-intent search queries and answers about installing and using this skill.
scRNA-seq quality control can be performed using MAD-based adaptive outlier detection on log1p_total_counts, log1p_n_genes_by_counts, and pct_counts_mt to identify and remove low-quality cells.
MAD-based adaptive thresholding is a data-driven method that calculates quality control cutoffs for scRNA-seq metrics, reducing reliance on fixed thresholds to filter low-quality cells.
Yes, the scRNA-seq QC workflow supports species-aware annotation, distinguishing between human (MT-/RPL/RPS) and mouse (mt-/Rpl/Rps) mitochondrial, ribosomal, and hemoglobin gene sets.
Yes, the MAD-based QC workflow applies directly to raw 10x data or .h5ad files to compute QC metrics, apply adaptive thresholding, and generate visualization plots prior to normalization.
After completing scRNA-seq quality control, the workflow recommends running downstream doublet-detection steps using compatible tools like scrublet or scDblFinder prior to HVG selection.
MAD-based QC should be used for scRNA-seq data when you need adaptive, data-driven thresholds to avoid the limitations of fixed cutoffs across varying datasets and experimental conditions.
Victory-HugoPerform end-to-end single-cell RNA-seq analysis with Scanpy.
anthropicsFilter low-quality cells from single-cell RNA-seq data using MAD-based QC.
tony-zhelonkinRun standard single-cell RNA-seq analysis with Scanpy on AnnData objects.
EpiphyticFilters low-quality cells from AnnData and 10X Genomics single-cell RNA-seq datasets using MAD-based thresholds.
